Solving the traveling salesman problem using genetic algorithms with the new evaluation function

Traveling salesman problem is of the known and classical problems at Research in Operations. Many scientific activities can be solved as traveling salesman problem. Existing methods for solving hard problems (such as the traveling salesman problem) consists of a large number of variables and constraints which reduces their practical efficiency in solving problems with the original size. In recent decades, the use of heuristic and meta-heuristic algorithms such as genetic algorithms is considered. Due to the simple structure of meta-heuristic algorithms that have shown greater ability is more used by researchers in operational research. In this study, the improved genetic algorithm is used to solve TSP that the difference of it with the standard genetic algorithm is in the evaluation function. The new evaluation function is from a common evaluation function and a new idea.